Face Enhancer Image API Documentation

Face Enhancer Image API Documentation

Playground

Restore and sharpen faces in any photo — recover natural detail in blurry, compressed or low-quality portraits in seconds. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Face Enhancer restores and sharpens faces in photos. It finds the faces in your image, recovers natural detail in eyes, skin, hair and teeth, and blends each restored face back seamlessly — the rest of the image stays exactly as it was.

Why Choose This?

• Automatic face detection Up to three of the largest faces in the image are enhanced; no masks or manual selection needed.

• Natural restoration Recovers detail lost to blur, compression and low resolution while keeping the person’s identity and expression.

• Occlusion aware Hands, hair strands and glasses in front of a face are preserved instead of being painted over.

• Everything else untouched Only the faces change; background, clothing and composition keep the original pixels and resolution.

Parameters

How to Use

1. Upload your image — a portrait, group photo or any picture with faces.
2. Choose the output format (optional).
3. Run — the enhanced image keeps the original resolution.
4. Download the result.

Pricing

Best Use Cases

• Old and low-quality photos — Bring back facial detail in scanned, compressed or blurry portraits.
• AI-generated images — Clean up soft or distorted faces in generated pictures.
• Social media & profiles — Sharper, clearer faces for avatars and posts.
• Group photos — Enhance the main faces in one pass.

Notes

• Up to 3 faces are enhanced per image — the largest ones.
• Output resolution equals input resolution; very small faces gain less detail than large ones.
• Works best on real human faces; illustrated or anime faces may not improve.
• Ensure you have permission to use all uploaded images and likenesses.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "output_format": "jpeg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/face-enhancer/image" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Request Parameters

Result Response Parameters